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利用公民科学数据评估蜱虫对人类的附着情况:2015年至2021年瑞士使用空间最大熵模型的时空映射。

Assessing tick attachments to humans with citizen science data: spatio-temporal mapping in Switzerland from 2015 to 2021 using spatialMaxent.

作者信息

Bald Lisa, Ratnaweera Nils, Hengl Tomislav, Laube Patrick, Grunder Jürg, Tischhauser Werner, Bhandari Netra, Zeuss Dirk

机构信息

Faculty of Geography, Environmental Informatics, University of Marburg, Deutschhausstraße 12, 35032, Marburg, Hessen, Germany.

Institute of Natural Resource Sciences, Zurich University of Applied Sciences ZHAW, Grüentalstrasse 14, 8820, Wädenswil, Zürich, Switzerland.

出版信息

Parasit Vectors. 2025 Jan 23;18(1):22. doi: 10.1186/s13071-024-06636-4.

DOI:10.1186/s13071-024-06636-4
PMID:39849565
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11759452/
Abstract

BACKGROUND

Ticks are the primary vectors of numerous zoonotic pathogens, transmitting more pathogens than any other blood-feeding arthropod. In the northern hemisphere, tick-borne disease cases in humans, such as Lyme borreliosis and tick-borne encephalitis, have risen in recent years, and are a significant burden on public healthcare systems. The spread of these diseases is further reinforced by climate change, which leads to expanding tick habitats. Switzerland is among the countries in which tick-borne diseases are a major public health concern, with increasing incidence rates reported in recent years.

METHODS

In response to these challenges, the "Tick Prevention" app was developed by the Zurich University of Applied Sciences and operated by A&K Strategy Ltd. in Switzerland. The app allows for the collection of large amounts of data on tick attachment to humans through a citizen science approach. In this study, citizen science data were utilized to map tick attachment to humans in Switzerland at a 100 m spatial resolution, on a monthly basis, for the years 2015 to 2021. The maps were created using a state-of-the-art modeling approach with the software extension spatialMaxent, which accounts for spatial autocorrelation when creating Maxent models.

RESULTS

Our results consist of 84 maps displaying the risk of tick attachments to humans in Switzerland, with the model showing good overall performance, with median values ranging from 0.82 in 2018 to 0.92 in 2017 and 2021 and convincing spatial distribution, verified by tick experts for Switzerland. Our study reveals that tick attachment to humans is particularly high at the edges of settlement areas, especially in sparsely built-up suburban regions with green spaces, while it is lower in densely urbanized areas. Additionally, forested areas near cities also show increased risk levels.

CONCLUSIONS

This mapping aims to guide public health interventions to reduce human exposure to ticks and to inform the resource planning of healthcare facilities. Our findings suggest that citizen science data can be valuable for modeling and mapping tick attachment risk, indicating the potential of citizen science data for use in epidemiological surveillance and public healthcare planning.

摘要

背景

蜱虫是众多人畜共患病原体的主要传播媒介,传播的病原体比任何其他吸血节肢动物都多。在北半球,近年来人类蜱传疾病病例,如莱姆病和蜱传脑炎有所增加,给公共卫生保健系统带来了沉重负担。气候变化导致蜱虫栖息地扩大,进一步加剧了这些疾病的传播。瑞士是蜱传疾病成为主要公共卫生问题的国家之一,近年来报告的发病率不断上升。

方法

为应对这些挑战,苏黎世应用科学大学开发了“蜱虫预防”应用程序,并由瑞士的A&K Strategy Ltd.运营。该应用程序允许通过公民科学方法收集大量关于蜱虫附着于人体的数据。在本研究中,利用公民科学数据以100米的空间分辨率,按月绘制2015年至2021年瑞士蜱虫附着于人体的地图。这些地图是使用具有软件扩展空间最大熵模型(spatialMaxent)的先进建模方法创建的,该方法在创建最大熵模型时考虑了空间自相关。

结果

我们的结果包括84张显示瑞士蜱虫附着于人体风险的地图,模型显示出良好的整体性能,中位数从2018年的0.82到2017年和2021年的0.92不等,空间分布令人信服,经瑞士蜱虫专家验证。我们的研究表明,蜱虫附着于人体的情况在定居区域边缘尤其严重,特别是在绿地较多、建筑稀疏的郊区,而在城市化密集地区则较低。此外,城市附近的森林地区也显示出较高的风险水平。

结论

此地图绘制旨在指导公共卫生干预措施,以减少人类接触蜱虫的机会,并为医疗设施的资源规划提供信息。我们的研究结果表明,公民科学数据对于建模和绘制蜱虫附着风险可能很有价值,表明公民科学数据在流行病学监测和公共卫生保健规划中的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/1d18dd4ba8b2/13071_2024_6636_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/1e896f22c958/13071_2024_6636_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/286682465ff2/13071_2024_6636_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/810d6a2411a5/13071_2024_6636_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/986c2f3dbf2f/13071_2024_6636_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/5393221c5003/13071_2024_6636_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/2a0722d7a8c8/13071_2024_6636_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/be35fa1ac4d8/13071_2024_6636_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/f486ca4863c4/13071_2024_6636_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/1d18dd4ba8b2/13071_2024_6636_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/1e896f22c958/13071_2024_6636_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/286682465ff2/13071_2024_6636_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/810d6a2411a5/13071_2024_6636_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/986c2f3dbf2f/13071_2024_6636_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/5393221c5003/13071_2024_6636_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/2a0722d7a8c8/13071_2024_6636_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/be35fa1ac4d8/13071_2024_6636_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/f486ca4863c4/13071_2024_6636_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bb1/11759452/1d18dd4ba8b2/13071_2024_6636_Fig9_HTML.jpg

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Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014-2021.英国伴侣动物蜱虫附着的风险因素:2014-2021 年时空分析。
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